Microbiome function predicts amphibian chytridiomycosis disease dynamics

Background The fungal pathogen Batrachochytrium dendrobatidis (Bd) threatens amphibian biodiversity and ecosystem stability worldwide. Amphibian skin microbial community structure has been linked to clinical outcome of Bd infections, yet its overall functional importance is poorly understood. Methods Microbiome taxonomic and functional profiles were assessed using high-throughput bacterial 16S rRNA and fungal ITS2 gene sequencing, bacterial shotgun metagenomics and skin mucosal metabolomics. We sampled 56 wild midwife toads (Alytes obstetricans) from montane populations exhibiting Bd epizootic or enzootic disease dynamics. In addition, to assess whether disease-specific microbiome profiles were linked to microbe-mediated protection or Bd-induced perturbation, we performed a laboratory Bd challenge experiment whereby 40 young adult A. obstetricans were exposed to Bd or a control sham infection. We measured temporal changes in the microbiome as well as functional profiles of Bd exposed and control animals at peak infection. Results Microbiome community structure and function differed in wild populations based on infection history and in experimental control versus Bd-exposed animals. Bd exposure in the laboratory resulted in dynamic changes in microbiome community structure and functional differences, with infection clearance in all but one infected animal. Sphingobacterium, Stenotrophomonas and an unclassified Commamonadaceae were associated with wild epizootic dynamics and also had reduced abundance in laboratory Bd-exposed animals that cleared infection, indicating a negative association with Bd resistance. This was further supported by microbe-metabolite integration which identified functionally relevant taxa driving disease outcome, of which Sphingobacterium and Bd were most influential in wild epizootic dynamics. The strong correlation between microbial taxonomic community composition and skin metabolome in the laboratory and field are inconsistent with microbial functional redundancy, indicating that wholesale differences in microbial taxonomy drive functional variation. Shotgun metagenomic analyses support these findings, with similar disease-associated patterns in beta diversity. Analysis of differentially abundant bacterial genes and pathways indicated that bacterial environmental sensing and Bd resource competition are important in driving infection outcome. Conclusions Bd infection drives altered microbiome taxonomic and functional profiles across laboratory and field environments. Our application of multi-omics analyses in experimental and field settings robustly predict Bd disease dynamics and identify novel candidate biomarkers of infection